Kiener, D.; Grosinger, W.; Dehm, G.; Pippan, R.: A further step towards an understanding of size-dependent crystal plasticity: In situ tenison experiments of miniaturized single-crystal copper samples. Acta Materialia 56 (3), pp. 580 - 592 (2008)
Inkson, B. J.; Dehm, G.; Peng, Y.: Dynamical growth of Cu-Pt nanowires with a nanonecklace morphology. Nanotechnology 18 (41), 415601, pp. 1 - 5 (2007)
Oh, S. H.; Legros, M.; Kiener, D.; Gruber, P. A.; Dehm, G.: In situ TEM straining of single crystal Au films on polyimide: Change of deformation mechanisms at the nanoscale. Acta Materialia 55 (16), pp. 5558 - 5571 (2007)
Kiener, D.; Motz, C.; Rester, M.; Jenko, M.; Dehm, G.: FIB damage of Cu and possible consequences for miniaturized mechanical tests. Materials Science and Engineering A: Structural Materials Properties Microstructure and Processing 459 (1-2), pp. 262 - 272 (2007)
Kiener, D.; Motz, C.; Schöberl, T.; Jenko, M.; Dehm, G.: Determination of mechanical properties of copper at the micron scale. Advanced Engineering Materials 8 (11), pp. 1119 - 1125 (2006)
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
Integrated Computational Materials Engineering (ICME) is one of the emerging hot topics in Computational Materials Simulation during the last years. It aims at the integration of simulation tools at different length scales and along the processing chain to predict and optimize final component properties.
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…
The project’s goal is to synergize experimental phase transformations dynamics, observed via scanning transmission electron microscopy, with phase-field models that will enable us to learn the continuum description of complex material systems directly from experiment.
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.